Erik Reinertsen

BME PhD Proposal Presentation

Location: Woodruff Memorial Building, Room 4004 (Department of Biomedical Informatics - classroom)

Date: Tue Apr 25th

Time: 3-4 pm EST

Committee members:

• Gari Clifford, DPhil (advisor)
• Shamim Nemati, PhD
• Amit Shah, MD, MSCR
• Eberhard Voit, PhD
• Lee Cooper, PhD

Title: "Signal processing and machine learning for estimating illness severity from physiological and behavioral data" 

Abstract: Heart rate and locomotor activity convey information about autonomic nervous system physiology and behavior. Signal processing methods can be applied to these data sources to derive features that differ in patients with mental and/or cardiovascular illness, compared to healthy controls. Machine learning algorithms trained on these features can classify illness, but accurate classification requires addressing factors such as noise, non-stationarity, and time scale in the data. Three studies are proposed to evaluate methods that account for these factors and improve classifier performance in the context of PTSD, schizophrenia, and heart failure.